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anibalrojosan/README.md

👋 Hi, I'm Aníbal

I'm a Bioprocess Engineer & MSc. in Biochemical Engineering transitioning into Full-stack Data Science 🦠🤖.

Learning journey

My main interests are:

  • 🚀 End-to-End ML: Bridging the gap between models and production via Full-stack engineering.
  • 📐 ML Foundations: Strengthening my math and coding skills and building classical algorithms from scratch.
  • 🏗️ Software Excellence: Implementing clean, scalable code for reproducible data science.
  • 🧠 Deep Learning: Mastering PyTorch for complex model development.

I'm currently expanding my full-stack toolkit to bridge the gap between data intelligence and user experience, integrating complex mathematics, data analysis and ML models into intuitive, scalable applications:

  • Frontend for Data: Learning HTML, CSS, JS/TS and React to transform static models into interactive data products.
  • Robust Backend: Deepening into FastAPI & Django to create scalable APIs that serve ML models efficiently.
  • Full-stack Integration: Understanding how to architect end-to-end systems where data flows from databases to a polished user interface.

Current projects

  • 🦠 ALBATwin-Hub - Digital Twin for Algae-Bacteria wastewater treatment in high rate algal ponds.
  • 🪙 Proggy Wallet - Full-stack Fintech roadmap; architecting atomic transactions and secure digital assets.
  • 📈 Optima - FinOps intelligence platform; orchestrating software lifecycle and cost optimization through decoupled architecture.
  • 😎 PepoRAG - 100% local technical librarian; chat with your books with this private RAG system.
  • 🎵 Spotify ML Analyzer - Unsupervised ML to decode your musical personality; AI-driven psychological profiling.
  • 📦 Ecommerce Shipping Delay Analysis - Quantifying the cost of shipping delays; from raw logistics to interactive insights.
  • 🚀 MLOps Workflow - Industrialized ML pipelines; transforming models into tested, containerized microservices.
  • 🎛️ Hyperparameter Tuning Toolkit - Quantifying the trade-offs of HPO strategies; where Optuna meets Evolutionary Algorithms.
  • 💎 Clean Income Prediction - Refactoring monolithic DS notebooks into production-grade modular ecosystems.

Some tools that I have been using and learning

Category
Technologies
Languages
Data Science & ML
Databases
Web Development
Visualization
DevOps & Infra uv Ruff

Pinned Loading

  1. proggy-wallet proggy-wallet Public

    A scalable Full-Stack Fintech blueprint evolving from prototype to enterprise architecture using Python, Django, Docker, and automated CI/CD pipelines.

    Python 1

  2. pepo-rag pepo-rag Public

    A 100% local technical librarian and assistant. Chat with your books while keeping your privacy

    Python

  3. ALBATwin-Hub ALBATwin-Hub Public

    A hybrid Digital Twin for Algae-Bacteria wastewater treatment in HRAP. Combines mechanistic ODE modeling (ALBA model) with Physics-Informed Neural Networks (PINNs) for process optimization and synt…

  4. ecommerce-shipping-delay-analysis ecommerce-shipping-delay-analysis Public

    Análisis end-to-end sobre el impacto de los tiempos de entrega en la satisfacción del cliente (ETL, EDA y Dashboard).

    Jupyter Notebook

  5. spotify-ml-analyzer spotify-ml-analyzer Public

    Full Stack Data Science app (Django + React) that decodes your musical DNA, analyzing Spotify audio features to visualize your mood and personality evolution.

    Python

  6. production-ready-mlops-workflow production-ready-mlops-workflow Public

    Production-ready MLOps infrastructure: demonstrating engineering best practices with reproducible pipelines, a robust API (Flask/Pydantic), Docker containers, and automated CI/CD with GitHub Actions.

    Jupyter Notebook 1